Assessing differences in legislators' revealed preferences: A case study on the 107th U.S. Senate

TL;DR

This paper introduces a Bayesian hierarchical model to analyze how external factors like party changes influence legislators' revealed preferences, using the 107th U.S. Senate as a case study.

Contribution

It extends spatial voting models with a Bayesian approach to test hypotheses about preference differences influenced by political context.

Findings

Party affiliation change may affect legislators' preferences.

Majority status change shows no significant effect.

Model provides a probabilistic framework for legislative preference analysis.

Abstract

Roll call data are widely used to assess legislators' preferences and ideology, as well as test theories of legislative behavior. In particular, roll call data is often used to determine whether the revealed preferences of legislators are affected by outside forces such as party pressure, minority status or procedural rules. This paper describes a Bayesian hierarchical model that extends existing spatial voting models to test sharp hypotheses about differences in preferences the using posterior probabilities associated with such hypotheses. We use our model to investigate the effect of the change of party majority status during the 107th U.S. Senate on the revealed preferences of senators. This analysis provides evidence that change in party affiliation might affect the revealed preferences of legislators, but provides no evidence about the effect of majority status on the revealed preferences of legislators.